Abstract

Airborne light detection and ranging (LiDAR) has played an important role in obtaining spatial information. But most existing LiDAR data classification algorithms mainly based on elevation and need more manual participation. Compared to these algorithms, we emphasize the use of intensity, RGB and echo number, and put forward a decision tree classification method. Before using this method, the intensity value must be calibrated first, and the RGB usually assigned from orthophoto. Then the experiment show that classification work can be completed with high accuracy while reducing manual workload. In addition, it was found intensity information is useful in target detection.